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Individuals with diagnoses of autism spectrum disorder (ASD) within criminal justice settings are a highly heterogeneous group. Although studies have examined differences between those with and without ASD in such settings, there has been no examination of differences within the ASD group. The paper aims to discuss these issues.

Drawing on the findings of a service evaluation project, this paper introduces a typology of ASD within forensic mental health and intellectual disability settings.

The eight subtypes that are described draw on clinical variables including psychopathy, psychosis and intensity/frequency of problem behaviours that co-occur with the ASD. The initial assessment of inter-rater reliability on the current version of the typology revealed excellent agreement, multirater Kfree =0.90.

The proposed typology could improve understanding of the relationship between ASD and forensic risk, identify the most appropriate interventions and provide prognostic information about length of stay. Further research to refine and validate the typology is ongoing.

This paper introduces a novel, typology-based approach which aims to better serve people with ASD within criminal justice settings.

The aim of the project was to evaluate the short‐term treatment outcomes of patients treated in a medium secure service for people with intellectual disability. A total of 138 patients, 77 discharged and 61 current inpatients, treated over a six‐year period were included in the audit. Information on demographic and clinical variables was collected on a pre‐designed data collection tool and analysed using appropriate statistical methods. The median length of stay for the discharged group was 2.8 years. About 90% of this group were discharged to lower levels of security and about a third went directly to community placements. None of the clinical and forensic factors examined was significantly associated with length of stay for this group. There was a ‘difficult to discharge long‐stay’ group which had more patients with criminal sections, restriction orders, history of abuse, fire setting, personality disorders and substance misuse. However, when regression analysis was done, most of these factors were not predictive of the length of stay. Clinical diagnosis or offending behaviour categories are poor predictors of length of hospital stay, and there is a need to identify empirically derived patient clusters using a variety of clinical and forensic variables. Common datasets and multi‐centre audits are needed to drive this.